Senior Infrastructure Software Engineer

As a Senior Infrastructure Software Engineer at Baseten, you will take charge of designing and architecting scalable infrastructure systems specifically for our ML inference platform. This includes leading the optimization of Kubernetes deployments for efficient model serving and enhancing our inference orchestration layer. You will also define monitoring strategies for performance and resource utilization, develop solutions for GPU capacity management, and establish automation standards to streamline ML deployment workflows. Your role will be pivotal in making key architectural decisions, mentoring junior engineers, and contributing to the long-term technical strategy of our infrastructure.

To qualify for the Senior Infrastructure Software Engineer position at Baseten, candidates should hold a Bachelor's degree or higher in Computer Science or a related field. Additionally, a minimum of 5 years of experience building production infrastructure systems is essential, alongside expert-level proficiency in Go. Experience with Kubernetes in production environments and familiarity with major cloud providers (AWS, GCP) are critical. A deep understanding of distributed systems concepts, observability systems design, and a track record of leading technical initiatives will greatly enhance your candidacy.

The work culture at Baseten is inclusive and supportive, aiming to foster a collaborative environment where learning and growth are prioritized. As a Senior Infrastructure Software Engineer, you'll be part of a remote-first culture that values diverse experiences and perspectives. You will have ample opportunities for personal development, exposure to various ML startups, and the chance to engage with innovative projects that are shaping the future of AI technologies.

Key technical skills for a Senior Infrastructure Software Engineer at Baseten include expert-level proficiency in Go, a strong understanding of Kubernetes, and experience with major cloud platforms such as AWS and GCP. Additionally, having a grasp of distributed systems concepts, performance tuning, and designing observability systems is important. Experience related to ML/AI workloads and familiarity with MLOps platforms will also be extremely valuable in this role.

Baseten is committed to the professional development of its Senior Infrastructure Software Engineers by providing numerous learning opportunities in a dynamic environment. The company encourages the mentoring of junior engineers, involvement in technical discussions, and contributions to long-term infrastructure strategies. Moreover, being part of a rapidly growing startup in an exciting engineering field allows you to stay at the forefront of technological advancement, enhancing your skills and expertise while working on impactful projects.

When answering this question, focus on specific projects where you've implemented or optimized Kubernetes. Discuss your role, any challenges you faced, and how you overcame them. Highlight your knowledge of scaling, security best practices, and the impact of your contributions to model serving efficiency.

For this question, consider discussing various techniques such as optimizing hyperparameters, employing parallel processing, and monitoring resource utilization. Provide examples from your experience that demonstrate your analytical skills in improving model performance and your understanding of the underlying infrastructure.

In answering, emphasize the importance of regular audits, implementing security protocols, and automating monitoring systems. Discuss any specific tools you have used and how you’ve applied best practices to maintain reliability and security across production systems.

Highlight a specific instance where you faced a tough technical decision in your career. Explain your thought process, the data you considered, and the eventual outcome. Show how your decision positively impacted project delivery, team dynamics, or system performance.

Emphasize your understanding of observability principles, including monitoring, tracing, and alerting. Discuss tools you have implemented to gain insights into system behavior and how you’ve used observability practices to troubleshoot performance issues in previous roles.

In your response, provide examples of how you’ve transitioned knowledge to junior engineers. Discuss approaches like code reviews, pair programming, or hosting workshops and how you determined effective mentoring techniques based on individual learning styles.

Reflect on current trends such as serverless architecture, AI-driven deployment tools, or advancements in distributed computing. Your answer should demonstrate your keen awareness of industry shifts and how they can affect Baseten's goals and infrastructure strategy.

Share specific examples of cloud services you've utilized from AWS or GCP. Describe projects where you leveraged specific functionalities such as database services, compute instances, or container orchestration. Highlight your ability to make cost-efficient decisions based on best cloud practices.

Explain your communication style and collaboration methods when working with cross-functional teams. Provide examples of how you align technical objectives with business goals and how you ensure mutual understanding throughout the project lifecycle.

Share your enthusiasm for the rapidly evolving field of AI and infrastructure capabilities. Discuss specific projects or technologies you’ve encountered that fueled your passion and how you envision contributing to advancing ML solutions at Baseten.